Pervasive Label Errors in ML Datasets Destabilize Benchmarks
To our surprise, label errors are pervasive across 10 popular benchmark test sets used in most machine learning research, destabilizing benchmarks.
machine-learning
A collection of 3 posts
Announcing cleanlab: a Python Package for ML and Deep Learning on Datasets with Label Errors
We often deal with label errors in datasets, but no common framework exists to support machine learning research and benchmarking with label noise. Announcing cleanlab: a Python package for finding label errors in datasets and learning with noisy labels. cleanlab...
An Introduction to Confident Learning: Finding and Learning with Label Errors in Datasets
This post overviews the paper Confident Learning: Estimating Uncertainty in Dataset Labels authored by Curtis G. Northcutt, Lu Jiang, and Isaac L. Chuang.